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Renewable Energy and Engineering Simulation

Renewable Energy came from the need to discover and develop alternative solutions to classic fossil energy based on nature recycling phenomena like wind power, solar bright, water force, post-volcanic emanations, or biofuel improvement. Other renewable power technology like waves, tidal, and electric cars are also emerging. R&D investments in the dynamic processes of renewable energy are contributing to dramatic reduction of production costs and quickly assimilation in the energy market.

Natural phenomena, new technologies, optimized design and processes

Let’s take a quick look at the most popular renewable energy solutions and specific process manufacturing characteristics for equipment and components:

Wind turbines

Wind turbines are used to generate electricity from the kinetic power of the wind. There are two main kinds of wind generators: using a vertical and a horizontal axis. Wind turbines can be used to generate large amounts of electricity in wind farms both onshore and offshore. Looking to the kinetic source, wind turbine design and optimization are mostly related to the airflow multiple analysis controlling the dimensions, the components profile, and land positioning in order to better adapt to local wind conditions. A wind turbine simulation with SimScale is shown a few paragraphs below.

A research team from several US universities and national laboratories is working on a gigantic wind structure. The turbine will rise nearly a third of a mile into the sky (approx. 480 m), will measure a quarter of a mile in diameter (402 m.), and will be equipped with two or three 656-foot (200 m.) blades that will span more than two football fields. Common industrial turbines have blades under 200 feet (61m.). The massive turbine will be higher than the Empire State Building and will produce 50 megawatts of energy [1].

Solar power photovoltaic simulation

The range of solar cells spans different materials and structures in the quest to extract maximum power from the device while keeping the cost to a minimum. Materials used today for the solar cells are: crystalline or amorphous silicon, thin film, cadmium telluride, and a copper-indium-gallium-selenide mix [2]. Assuming mathematical simplification specific for simulation algorithms, the best way to improve the efficiency of photovoltaic (PV) systems is to optimize the size, structure, and shadow positioning of solar panels. Optimizing PV systems should solve a set of simulation challenges related to: light intensity and incidence angle, environmental temperature variation, connection losses minimization, and lower the production costs.

Underwater tidal turbine. Source: Marine Current Turbines, Ltd.

Hydro power

It is produced by using electricity generators to extract energy from moving water. Hydrogeologists and water power engineers are looking for permanent process improvements. Wave, tidal, and ocean energy technologies are just beginning to reach viability as potential commercial power sources. Special buoys, turbines, and other underwater technologies can capture the power of waves and tides and convert it into clean, pollution-free electricity. Like other renewable resources, both wave and tidal energy are variable in nature. [3].

Geothermal energy

Geothermal energy is created by harnessing geothermal energy from the earth. Any geothermal power plant use a source of steam coming from the 1-2 km deep underground thermal reservoirs and raising to the surface though bore holes. Depending on the source, the steam from the wells can be dry or moist. Wet steam passes through moisture separators where the used water is going for reinjection back to the underground reservoir. After that, the main steam goes to the turbine which have special requirements. This equipment is subject to process improvement and optimization by using thermodynamic and CFD analyses.

Biomass Energy optimization

Biofuels are produced from living organisms or from renewable process of food waste stocks. Growing of energy demands requests more sustainable sources of biomass and more efficient conversion processes. Automation systems that support advanced process control strategies can help producers optimize every step of their process and position them to capitalize on the potential opportunities of biomass power generation — resulting in increased operational efficiency, lower total cost of ownership, and environmental sustainability [4].

SimScale — a valuable tool in renewable energy equipment optimization

The SimScale simulation platform enables the renewable energy providers to better understand the physical phenomena, to simulate more efficient manufacturing processes, and to optimize industrial equipment or various machinery types. Providing a full range of analyses from fluid dynamics and structural mechanics to thermodynamics or particles, SimScale offers a large area of functionalities for the process improvement in the renewable energy industry.

There is a wide range of renewable energy equipment that can benefit from SimScale. From turbines, rotors, blades and other components to photovoltaic panels, valves, recipients, junctions, boilers and heating machines, product designs can be virtually tested and optimized in less time and at lower cost.

This key study project demonstrates how a certain configuration of a wind turbine can be simulated. The external flow around a rotor is simulated and the forces acted by the air upon the rotor are computed. Using the Multi Reference Frame (MRF) method, the rotational motion of the rotor is ensured. The picture depicts the air speed near the blades and shows how the streamlines are curved in the vicinity of the rotor. The calculated forces and moments can be used to evaluate the turbine power.

Rotor eigenfrequency analysis – In this project, the eigenfrequencies and the corresponding eigenmodes of a rotor have been computed with SimScale. The simulation has been set up using the frequency analysis type which allows a straightforward setup of all boundary conditions and other simulation settings. Final model provide the numerical values of the eigenfrequencies, allowing also the visualization of the displacement behavior for the corresponding eigenmodes of the rotor.

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